Predicting the Future
Completing Models of Observed Complex Systems
Published on 23. August 2016
Book
Paperback/Softback
XVI, 238 pages
978-1-4939-5238-0 (ISBN)
Description
Through the development of an exact path integral for use in transferring information from observations to a model of the observed system, the author provides a general framework for the discussion of model building and evaluation across disciplines. Through many illustrative examples drawn from models in neuroscience, geosciences, and nonlinear electrical circuits, the concepts are exemplified in detail. Practical numerical methods for approximate evaluations of the path integral are explored, and their use in designing experiments and determining a model's consistency with observations is explored.
More details
Series
Edition
Softcover reprint of the original 1st ed. 2013
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Illustrations
91 farbige Abbildungen, 6 s/w Abbildungen
XVI, 238 p. 97 illus., 91 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 15 mm
Weight
394 gr
ISBN-13
978-1-4939-5238-0 (9781493952380)
DOI
10.1007/978-1-4614-7218-6
Schweitzer Classification
Other editions
Additional editions
Book
06/2013
Springer
€106.99
Shipment within 15-20 days
Person
Henry Abarbanel is a new member of the Springer Complexity Board. He is a Professor of Physics at UCSD in La Jolla, CA. http: //neurograd.ucsd.edu/faculty/detail.php?id=1
Content
Preface.- 1 An Overview; The Challenge of Complex Systems.- 2 Examples as a Guide to the Issues.- 3 General Formulation of Statistical Data Assimilation.- 4 Evaluating the Path Integral.- 5 Twin Experiments.- 6 Analysis of Experimental Data.